Genotype–phenotype spectrum and correlations in <scp>Xia‐Gibbs</scp> syndrome: Report of five novel cases and literature review
Bibliographic record
Abstract
BACKGROUND: Xia-Gibbs syndrome (XGS) is a rare neurodevelopmental disorder caused by pathogenic variants in the AT-hook DNA-binding motif-containing 1 gene (AHDC1), encoding a protein with a crucial role in transcription and epigenetic regulation, axonogenesis, brain function, and neurodevelopment. AHDC1 variants possibly act through a dominant-negative mechanism and may interfere with DNA repair processes, leading to genome instability and impaired DNA translesion repair. Variants affecting residues closer to the N-terminal are thought to determine a milder phenotype with better cognitive performances. However, clean-cut genotype-phenotype correlations are still lacking. CASES: In this study, we investigated five subjects with XGS in whom exome sequencing led to the identification of five novel de novo pathogenic variants in AHDC1. All variants were extremely rare and predicted to cause a loss of protein function. The phenotype of the reported patients included developmental delay, hypotonia, and distinctive facial dysmorphisms. Additionally, uncommon clinical features were observed, including congenital hypothyroidism and peculiar skeletal abnormalities. CONCLUSIONS: In this study, we report uncommon XGS features associated with five novel truncating variants in AHDC, thus expanding the genotype and phenotypic spectrum of this complex condition. We also compared our cases to previously reported cases, discussing the current status of genotype-phenotype correlations in XGS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".